Who should use the Connect to Data Sources workflow?
Teams or solo builders working on data tasks who want a repeatable process instead of one-off tool experiments.
Execution Map
7-step pipeline — follow each step in order
1Setup · Step 1 of 7
Open task pageConnecting to Multiple Data Sources (Snowflake, BigQuery, etc.)
Prepare inputs and settings through Connecting to Multiple Data Sources (Snowflake, BigQuery, etc.) before running connect to data sources.
Why this matters
Connecting to Multiple Data Sources (Snowflake, BigQuery, etc.) sets up the foundation for connect to data sources; clean inputs here reduce downstream rework.
What you get
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
2Input · Step 2 of 7
Open task pageIntegrate data sources
Use Integrate data sources to build supporting assets that improve connect to data sources quality.
Why this matters
Integrate data sources strengthens connect to data sources by feeding better supporting material into the pipeline.
What you get
Supporting assets from integrate data sources are prepared and connected to the main workflow.
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3Input · Step 3 of 7
Open task pageAggregate diverse alternative data sources
Use Aggregate diverse alternative data sources to build supporting assets that improve connect to data sources quality.
Why this matters
Aggregate diverse alternative data sources strengthens connect to data sources by feeding better supporting material into the pipeline.
What you get
Supporting assets from aggregate diverse alternative data sources are prepared and connected to the main workflow.
4Core · Step 4 of 7
Open task pageConnect to Data Sources
Execute connect to data sources with Connect to Data Sources to produce the primary decision-ready insight.
Why this matters
This is the core step where connect to data sources actually happens, so it determines baseline quality for everything after it.
What you get
A first-pass decision-ready insight is generated and ready for refinement in the next steps.
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5Refine · Step 5 of 7
Open task pageImport data from multiple sources
Refine and validate connect to data sources output using Import data from multiple sources before final delivery.
Why this matters
Import data from multiple sources adds quality control so issues are caught before the workflow is finalized.
What you get
The decision-ready insight is improved, validated, and prepared for final delivery.
6Refine · Step 6 of 7
Open task pageData Extraction
Refine and validate connect to data sources output using Data Extraction before final delivery.
Why this matters
Data Extraction adds quality control so issues are caught before the workflow is finalized.
What you get
The decision-ready insight is improved, validated, and prepared for final delivery.
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7Deliver · Step 7 of 7
Open task pageData Analysis
Package and ship the output through Data Analysis so connect to data sources reaches end users.
Why this matters
Data Analysis is what turns intermediate output into a usable, publishable result for real users.
What you get
A finalized decision-ready insight is ready for publishing, handoff, or integration.